In wireless communication systems, the use of antenna arrays at the base station has been shown to increase both range, through increased gain, and capacity, through interference suppression. With adaptive antenna arrays, the signals received by multiple antenna elements are weighted and combined to improve system performance, e.g., by maximizing the desired receive signal power and/or suppressing interference. The performance of an adaptive antenna array increases dramatically with the number of antennas. Referring to an article entitled, "The Impact of Antenna Diversity on the Capacity of Wireless Communication Systems," by J. H. Winters, R. D. Gitlin and J. Salz, in IEEE Trans. on Communications, April 1994, it is shown that using an M element antenna array with optimum combining of the received signals can eliminate M-1 interferers and achieve an M-N fold diversity gain against multipath fading, resulting in increased range.
Most base stations today, however, utilize only two receive antennas with suboptimum processing, e.g., selection diversity where the antenna having the larger signal power is selected for reception and processing. It is desirable to be able to modify existing base stations to accommodate larger arrays of antennas and/or improved received signal combining techniques. However, modifying existing equipment is difficult, time consuming, and costly, in particular since equipment currently in the field is from a variety of vendors.
One alternative is to utilize an applique, which is an outboard signal processing box, interposed between the current base antennas and the input to the base station, which adaptively weights and combines the received signals fed to the base station, optionally utilizing additional antennas. FIG. 1 shows a base station utilizing an applique. A key to the viability of utilizing the applique approach is that it should require little, if any, modification of the base station equipment. This constraint implies that the processing performed by the applique should appear to the existing base station as a high-quality received signal from a single antenna.
The signal processing functions performed by an adaptive array are typically designed to maximize the signal to interference-plus-noise ratio. One well known method for accomplishing this is by adjusting the adaptive array weights so as to minimize the mean squared error of the output signal with respect to a reference signal. Two common techniques for reference signal generation that are well known in the art are coherent reference and constant-modulus reference, the latter also being known in the art as the constant-module algorithm (CMA).
Coherent reference is based on either a prior knowledge of the transmitted symbol sequence, or, when the transmitted symbols are unknown, simple slicing of the received data samples. If the transmitted symbol, say a.sub.n is known a priori, then the coherent reference sample corresponding to that symbol is just a.sub.n. If the transmitted symbol is not known a priori, then the coherent reference sample corresponding to the received sample y.sub.n is simply the constellation point which is closest to y.sub.n.
The constant-modulus algorithm exploits the fact that many systems of interest utilize phase modulation, in which all the points in the constellation have constant modulus or magnitude, say R. The constant-modulus reference signal value corresponding to a received sample y.sub.n is chosen to be that point on a circle of radius R which is closest to y.sub.n.
The primary advantages of utilizing coherent reference are its simplicity and the fact that it utilizes all of the information in the y.sub.n, both the magnitude and phase. Coherent reference consequently permits rapid tracking in environments in which both amplitude and phase are time varying, such as the Rayleigh fading channel.
One disadvantage of coherent reference is that it requires either a priori knowledge, or reliable sliced estimates of the transmitted symbol sequence. If such estimates are in error, the reference signal is incorrect and the true mean squared error is not minimized. If estimation errors occur frequently, or in bursts, the adaptive array weights can diverge rapidly from the correct settings, resulting in severe performance degradation.
Another disadvantage of coherent reference is related to its embodiment of signal phase information. Because of this, coherent reference is susceptible to rapid phase fluctuations due to sources other than the channel itself, such as receiver carrier estimation errors. For many systems of interest, the carrier frequency offset may be comparable to or greater than the maximum rate of phase change due to channel fading. However, using coherent reference, the weights track phase rotation regardless of its source. Thus, the presence of large frequency offsets can degrade the array's ability to handle true channel fluctuations due to fading.
One advantage of using constant-modulus reference is that it is inherently "blind", that is, it requires no knowledge of the transmitted symbol sequence. It is also completely insensitive to phase fluctuations. However, because constant-modulus reference throws the away phase information from the y.sub.n, its tracking performance is also fundamentally slower than coherent reference. Another significant disadvantage of constant-modulus reference is that since it exploits only the knowledge that the transmitted signal is constant modulus and ignores the actual symbol values, it is not capable of distinguishing between a desired constant-modulus signal and an interfering signal which is also constant modulus, e.g. another phase-modulated signal. Thus, an adaptive array employing constant-modulus reference can "lock on" to a constant modulus interfering signal and reject or cancel the desired signal.
In light of the above considerations there is therefore a need for combining coherent reference and constant modulus reference generation so as to take advantage of both techniques.